Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [21]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [22]:
#load data
df = px.data.gapminder()
df.head()
Out[22]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [24]:
df_2007 = df.query('year==2007')

df_2007_new = df_2007.groupby('continent').sum()
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Africa', 'Americas', 'Asia', 'Europe', 'Oceania'])

fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
df_2007 = df.query('year==2007')

df_2007_new = df_2007.groupby('continent').sum().sort_values('pop', ascending=True)
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Oceania', 'Europe', 'Americas', 'Africa', 'Asia'], 
           )

fig.show()

Question 3:¶

Add text to each bar that represents the population

In [5]:
df_2007 = df.query('year==2007')

df_2007_new = df_2007.groupby('continent').sum().sort_values('pop', ascending=True)
fig=px.bar(df_2007_new, x='pop', y=df_2007_new.index, color=['Oceania', 'Europe', 'Americas', 'Africa', 'Asia'],
           text_auto=True)

fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [11]:
df = px.data.gapminder()
fig = px.histogram(df, 
             x="pop",
             y="continent", 
             animation_frame="year",
             color="continent",  range_x=[0,4000000000])

fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [42]:
df = px.data.gapminder()
fig = px.histogram(df, 
             x="pop",
             y="country", 
             animation_frame="year",
             color="continent",  range_x=[0,1400000000]).update_yaxes(categoryorder="total ascending")
fig.update_layout(xaxis_title = 'pop')
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [41]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", y="country", animation_frame="year",
             color="continent",  range_x=[0,1400000000]).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False, autosize = False, width=1000, height=1000)
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [52]:
df = px.data.gapminder()
fig = px.histogram(df, x="pop", y="country", animation_frame="year",
             color="continent",  range_x=[0,1400000000],range_y = [131.5, 141.5]).update_yaxes(categoryorder="total ascending")

fig.update_layout(xaxis_title = 'pop', showlegend = False, autosize = False, width=1000, height=1000)
fig.show()
In [ ]: